Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)
Given the ubiquity of handwritten documents in human transactions, Optical Character Recognition (OCR) of documents have invaluable practical worth. Optical character recognition is a science that enables to translate various types of documents or images into analyzable, editable and searchable data...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9151144/ |
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| _version_ | 1849469693322067968 |
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| author | Jamshed Memon Maira Sami Rizwan Ahmed Khan Mueen Uddin |
| author_facet | Jamshed Memon Maira Sami Rizwan Ahmed Khan Mueen Uddin |
| author_sort | Jamshed Memon |
| collection | DOAJ |
| description | Given the ubiquity of handwritten documents in human transactions, Optical Character Recognition (OCR) of documents have invaluable practical worth. Optical character recognition is a science that enables to translate various types of documents or images into analyzable, editable and searchable data. During last decade, researchers have used artificial intelligence/machine learning tools to automatically analyze handwritten and printed documents in order to convert them into electronic format. The objective of this review paper is to summarize research that has been conducted on character recognition of handwritten documents and to provide research directions. In this Systematic Literature Review (SLR) we collected, synthesized and analyzed research articles on the topic of handwritten OCR (and closely related topics) which were published between year 2000 to 2019. We followed widely used electronic databases by following pre-defined review protocol. Articles were searched using keywords, forward reference searching and backward reference searching in order to search all the articles related to the topic. After carefully following study selection process 176 articles were selected for this SLR. This review article serves the purpose of presenting state of the art results and techniques on OCR and also provide research directions by highlighting research gaps. |
| format | Article |
| id | doaj-art-76af4aa2c72e409d9ccb5fa3eb545ebf |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-76af4aa2c72e409d9ccb5fa3eb545ebf2025-08-20T03:25:23ZengIEEEIEEE Access2169-35362020-01-01814264214266810.1109/ACCESS.2020.30125429151144Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)Jamshed Memon0https://orcid.org/0000-0001-8314-5333Maira Sami1https://orcid.org/0000-0003-1936-1722Rizwan Ahmed Khan2https://orcid.org/0000-0003-0819-800XMueen Uddin3https://orcid.org/0000-0003-1919-3407School of Computing, Quest International University Perak, Ipoh, MalaysiaDepartment of Computer Science, Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology, Karachi, PakistanFaculty of IT, Barrett Hodgson University, Karachi, PakistanDepartment of Software Engineering, Faculty of Science and Technology, Ilma University, Karachi, PakistanGiven the ubiquity of handwritten documents in human transactions, Optical Character Recognition (OCR) of documents have invaluable practical worth. Optical character recognition is a science that enables to translate various types of documents or images into analyzable, editable and searchable data. During last decade, researchers have used artificial intelligence/machine learning tools to automatically analyze handwritten and printed documents in order to convert them into electronic format. The objective of this review paper is to summarize research that has been conducted on character recognition of handwritten documents and to provide research directions. In this Systematic Literature Review (SLR) we collected, synthesized and analyzed research articles on the topic of handwritten OCR (and closely related topics) which were published between year 2000 to 2019. We followed widely used electronic databases by following pre-defined review protocol. Articles were searched using keywords, forward reference searching and backward reference searching in order to search all the articles related to the topic. After carefully following study selection process 176 articles were selected for this SLR. This review article serves the purpose of presenting state of the art results and techniques on OCR and also provide research directions by highlighting research gaps.https://ieeexplore.ieee.org/document/9151144/Optical character recognitionclassificationlanguagesfeature extractiondeep learning |
| spellingShingle | Jamshed Memon Maira Sami Rizwan Ahmed Khan Mueen Uddin Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR) IEEE Access Optical character recognition classification languages feature extraction deep learning |
| title | Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR) |
| title_full | Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR) |
| title_fullStr | Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR) |
| title_full_unstemmed | Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR) |
| title_short | Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR) |
| title_sort | handwritten optical character recognition ocr a comprehensive systematic literature review slr |
| topic | Optical character recognition classification languages feature extraction deep learning |
| url | https://ieeexplore.ieee.org/document/9151144/ |
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